Currently, when users perform searches for local businesses using a search engine, the ranking of the search results is static. That is, the search results only depend on location, and remain the same independent of the time when a query is submitted, the user who submitted the query, and other contextual information surrounding the search. Such contextual information can include, for example, weather, traffic, the popularity of a business and so forth. For instance, local search results for the query “restaurants” at a given location remain the same independent of when the query is submitted. However, users, especially those who submit queries from mobile devices, usually look for different types of restaurants in the morning, at noon or at night. In addition, depending on the personal preferences of the user different types of restaurants might be preferable at different times of day.
Searches for local businesses and other points of interest, especially those that come from mobile computing devices, such as smart phones, reflect users' interests “right here right now.” But, the current techniques for ranking local search results fail to capture these temporal, and contextual dynamics.